Sungpill Choi

908 citations
36 papers · 682 indexed · h-index 14

Sungpill Choi

34 papers receiving 659 citations

Peers

Sungpill Choi
Comparison fields: 5 of 71
  • Computer Vision and Pattern Recognition 324
  • Hardware and Architecture 63
  • Electrical and Electronic Engineering 438
  • Human-Computer Interaction 29
  • Artificial Intelligence 154
Replace Kyeongryeol Bong with:
Kyeongryeol Bong South Korea
Jong Hwan Ko South Korea
Shuanglong Liu United Kingdom
Hongxiang Fan United Kingdom
Hong Cai United States
Syed Shakib Sarwar United States
Zhengang Li United States
Guanglie Zhang Hong Kong
Zhiqiang Que United Kingdom
Kuizhi Mei China
Sungpill Choi relative to Kyeongryeol Bong South Korea Kyeongryeol Bong's profile →
Citations per field
00.5×2.9×
Kyeongryeol Bong · 1×
Citations per year

Countries citing papers authored by Sungpill Choi

Since Specialization
Citations

This map shows the geographic impact of Sungpill Choi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sungpill Choi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungpill Choi more than expected).

Fields of papers citing papers by Sungpill Choi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sungpill Choi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sungpill Choi. The network helps show where Sungpill Choi may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Sungpill Choi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sungpill Choi Line = papers co-authored together Sungpill Choi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202011
2 202013
3 20193
4 201929
5 201946
6 201845
7 20181
8 2017106
9 201724
10
A 0.62mW Ultra-low-power Convolutional Neural Network Face Recognition Processor and a CIS Integrated with Always-on Haar-like Face Detector
20178
11 201784
12 201634
13 201622
14
A 1.93 TOPS/W Scalable Deep Learning/Inference Processor with Tetra-parallel MIMD Architecture for Big Data Applications
201534
15 201578
16 20151
17 20151
18 201410
19 20132
20
IP-RFID based small ship management system
20091

About Sungpill Choi

Sungpill Choi is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Human-Computer Interaction, having authored 36 papers that have together received 682 indexed citations. Recurring topics across this work include CCD and CMOS Imaging Sensors (10 papers), Advanced Memory and Neural Computing (9 papers), Advanced Neural Network Applications (6 papers), Internet of Things and Social Network Interactions (6 papers), Advanced Image and Video Retrieval Techniques (6 papers), Robotics and Sensor-Based Localization (5 papers), Marine and Coastal Research (4 papers) and Advanced Vision and Imaging (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (324 citations), Hardware and Architecture (63 citations) and Electrical and Electronic Engineering (438 citations). Sungpill Choi has collaborated with scholars based in South Korea. Frequent co-authors include Hoi‐Jun Yoo, Kyeongryeol Bong, Changhyeon Kim, Sanghoon Kang, Donghyeon Han, Dongjoo Shin, Jinmook Lee, Seong‐Wook Park, Kyuho Lee and Youchang Kim. Their work appears in journals such as IEEE Journal of Solid-State Circuits, Applied Surface Science and IEEE Transactions on Circuits and Systems I Regular Papers.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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